THEORETICAL REVIEW

On the relation between theory of mind and executive functioning:A developmental cognitive neuroscience perspective

Mark Wade1& Heather Prime2

& Jennifer M. Jenkins3 & Keith O. Yeates4 & Tricia Williams5 & Kang Lee6

Published online: 4 April 2018# Psychonomic Society, Inc. 2018

AbstractTheory of mind (ToM) and executive functioning (EF) show marked interrelatedness across childhood, and developmentalpsychologists have long been interested in understanding the nature of this association. The present review addresses this issuefrom a cognitive neuroscience perspective by exploring three hypotheses regarding their functional overlap: (1) ToM relies on EF(EF→ToM); (2) EF relies on ToM (ToM→EF); and (3) ToM and EF are mutually related, owing to shared neural structures ornetworks (ToM↔EF). Drawing on evidence from normative brain development, neurodevelopmental and neurodegenerativediseases, patient lesion studies, and brain-imaging studies, we suggest that only a strict version of the ToM↔EF proposal ofcomplete neural overlap can be confidently ruled out on the basis of existing evidence. The balance of evidence suggests thatseparable neurobiological mechanisms likely underlie ToM and EF, with shared mechanisms for domain-general processing thatsupport both abilities. We highlight how future studies may empirically substantiate the nature of the ToM–EF relationship usingvarious biobehavioral approaches.

Keywords Theory of mind . Executive functioning . Cognitive neuroscience . Neuropsychological . Neuroimaging . Braindevelopment

Theory of mind and executive functioning: Abrief introduction

Two important capacities that show substantial develop-ment during the preschool years are theory of mind

(ToM) and executive functioning (EF; Garon, Bryson, &Smith, 2008; Wellman, Cross, & Watson, 2001). ToM isthe social–cognitive ability to understand human actions interms of the psychological states that motivate behavior,such as beliefs, emotions, desires, and intentions. EF refersto the cognitive processes that facilitate goal-directed ac-tion and problem solving, such as working memory, cog-nitive flexibility, inhibitory control, and self-monitoring(Anderson, 2002; Carlson, 2005). EF skills are importantfor the conscious, effortful control of thoughts and behav-ior (Oh & Lewis, 2008). Impairments in ToM and EF areassociated with a range of neurodevelopmental and psychi-atric conditions across the lifespan (Geurts, Verté,Oosterlaan, Roeyers, & Sergeant, 2004; Moritz et al.,2002; Pilowsky, Yirmiya, Arbelle, & Mozes, 2000;Schenkel, Marlow-O’Connor, Moss, Sweeney, &Pavuluri, 2008). Thus, uncovering the neurological basisof these cognitive abilities has implications for understand-ing both typical and atypical development, including howparticular brain structures or functions may forecast theemergence of neurodevelopmental problems characterizedby ToM and EF deficits (see Emerson et al., 2017, for arecent empirical example).

* Mark Wademark.wade@childrens.harvard.edu

1 Division of Developmental Medicine, Boston Children’s Hospital ofHarvard Medical School, 1 Autumn Street, R-533,Boston, MA 02215, USA

2 Department of Psychiatry and Behavioural Neurosciences,McMaster University, Hamilton, Ontario, Canada

3 Department of Applied Psychology and Human Development,University of Toronto, Toronto, Ontario, Canada

4 Department of Psychology, Hotchkiss Brain Institute, and AlbertaChildren’s Hospital Research Institute, University of Calgary,Calgary, Alberta, Canada

5 Department of Psychology, Hospital for Sick Children,Toronto, Ontario, Canada

6 Dr Eric Jackman Institute of Child Study, University of Toronto,Toronto, Ontario, Canada

Psychonomic Bulletin & Review (2018) 25:2119–2140https://doi.org/10.3758/s13423-018-1459-0

The purpose of this review is to apply a cognitive neuro-science lens to the study of ToM and EF co-development byoutlining the shared and distinct neural correlates of each, withthe intention of better accounting for their behavioral overlap.Our primary interest is childhood, since this is the epoch dur-ing which advances in these skills are most dramatic and thatportends significant growth in these and other functional out-comes later in life (Apperly,Warren, Andrews, Grant, & Todd,2011; Casey et al., 2011; Eigsti et al., 2006). Notwithstandingthe suggestion that mental state inference may be achievableto some degree by infants (Baillargeon, Scott, & He, 2010),our focus is on ToM and EF beyond this early period, giventhe paucity of literature examining infant brain activity duringtasks assessing these competencies (see Grossmann, 2015, fora review). In reference to ToM, we narrowly concentrate ontraditional measures that probe the understanding of desire,emotion, and belief (i.e., false belief), as opposed to broaderconceptualizations that entail abilities such as deception, ly-ing, humor, sarcasm, and so forth. With respect to EF, weconcentrate on Btop-down^ cognitive operations that can bedeployed in the service of an internal goal, similar to notionsof Bcognitive control^ or Beffortful control^ (see Nigg, 2017,for a review); thus, we tend not to include processes such asplanning, organization, and strategy formation. Althoughthese time-bound and definitional parameters confine our re-view and its conclusions, our aim is to provide a starting pointfrom which more elaborate proposals may advance.

The behavioral dilemma: Predictive relationsbetween ToM and EF

Developmental psychologists have long been interested in theassociation between ToM and EF, in part because they appearto develop in concert with one another. ToM and EF share awell-established behavioral link during the preschool period,with countless observational studies showing cross-sectionalassociations between these abilities (Carlson, Moses, &Breton, 2002; Hughes, 1998). The exact nature of this rela-tionship remains elusive. Nearly two decades ago, Perner andLang (1999) reviewed five theoretical accounts on the relationbetween ToM and EF. Three of these theories remain ongoingareas of debate and comprise the foundation of this review: (1)ToM depends on EF (EF→ToM), (2) EF depends on ToM(ToM→EF), and (3) ToM and EF are reciprocally related ow-ing to shared brain regions or neural networks (ToM↔EF).

The idea behind Proposal 1 (EF→ToM) is that EF skillssuch as self-monitoring and inhibitory control are necessary tounderstand the mental states of oneself and others (Carlson &Moses, 2001). More specifically, Russell (1996) argues thatself-monitoring—a facet of executive control—is required forself-awareness, and self-awareness is a prerequisite for ToM.Furthermore, the ability to inhibit and shift perspectives seems

necessary to understand the mental states of others. Followingthe general idea that EF supports the development of ToM,ample longitudinal evidence now exists that early EF is arobust predictor of later ToM reasoning in childhood(Carlson, Mandell, & Williams, 2004; Hughes & Ensor,2007; Marcovitch et al., 2015; Müller, Liebermann-Finestone, Carpendale, Hammond, & Bibok, 2012).

The rationale behind Proposal 2 (ToM→EF) is thatrepresenting the mental states of oneself and others is requiredin order to strategically control thoughts and behavior. In otherwords, EF tasks such as those requiring inhibitory controlnecessitate an awareness that the mental blueprints for actionsare causally effectual. With the understanding that mentalstates are causally linked to behavior, children acquire theability to exert executive control over interfering or unwantedaction tendencies (Lang & Perner, 2002; Perner & Lang,1999; Perner, Stummer, & Lang, 1999). This first requiresthe capacity to differentiate self from other, followed by abasic understanding of the relation between mental statesand behavior (meta-representation). This awareness that men-tal states are the drivers of behavior provides the basis onwhich those states can be manipulated to control thoughtsand actions. Although the preponderance of behavioral evi-dence favors the proposition that EF is directionally linked tolater ToM, several longitudinal studies suggest that early ToM,or its developmental precursors, also predicts later EF(Hughes & Ensor, 2007; McAlister & Peterson, 2013;Müller et al., 2012; Wade, Browne, Plamondon, Daniel, &Jenkins, 2016).

Finally, Proposal 3 of a Bcommon neural basis^ of ToM andEF (ToM↔EF) was initially forwarded by researchers exam-ining the etiology of autism and its associated neurocognitivedysfunctions. Observations of pronounced concurrent impair-ments in both ToM and EF in these children led various re-searchers to propose that a common neural architecture, par-ticularly involving prefrontal cortical regions, supported thesecognitive abilities (Ellis & Gunter, 1999; Ozonoff,Pennington, & Rogers, 1991). On this basis, we would expectToM and EF deficits to be interdependent, and by extension,we would expect these abilities to be reciprocally predictive ofone another. Empirical support for a bidirectional relation be-tween ToM and EF also exists (Austin, Groppe, & Elsner,2014; Hughes & Ensor, 2007; Müller et al., 2012).

To date, developmental psychologists have relied exten-sively on behavioral evidence to draw inferences about therelative plausibility of these three proposals. However, evenwith sophisticated longitudinal designs using cross-laggedmodels and robust confound-controls, the research continuesto yield mixed results. Moreover, since Perner and Lang’s(1999) seminal article, there has been an eruption of neurosci-entific inquiry into the nature of both ToM and EF develop-ment, which has been paced by advances in neuroimaging andother tools for assessing brain structure and function. Indeed,

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an entire field centered on Bsocial cognitive neuroscience^ hasemerged, with dedicated publication outlets (e.g., SocialNeuroscience, Social Cognitive and Affective Neuroscience),including those focused on childhood and adolescence (e.g.,Developmental Cognitive Neuroscience) (see Lieberman,2007). As of this writing, however, there has been no compre-hensive review on the developmental overlap between ToMand EF from a cognitive neuroscience perspective. Aside fromcrude and generalized suppositions concerning the neural un-derpinnings of ToM and EF, developmentalists have rarelyaimed to understand the relationship of these capacities interms of shared and/or distinct neural substrates. This is animportant endeavor, since psychologists aiming to uncoverthe etiological basis of conditions characterized by ToM andEF deficits often wish to elucidate the mechanisms underlyingthese problems. For instance, determining whether psychoso-cial stress (Noble, Norman, & Farah, 2005; Wade et al., 2016)or biomedical risk factors (Wade, Browne, Madigan,Plamondon, & Jenkins, 2014; Wade & Jenkins, 2016) im-pinge on ToM and EF through similar or disparate neuralmechanisms has implications for understanding the nature ofneurocognitive impairment and its relation to more complexdevelopmental and psychiatric outcomes. Similarly, identify-ing the directionality of these associations has meaningfulclinical implications with respect to targeting treatment towardfundamental cognitive skills that support development acrossdomains. Thus, in this review we draw on evidence fromcognitive neuroscience to clarify which proposals regardingthe ToM–EF relationship appear most credible on the basis ofexisting evidence. In doing so, we address gaps in the litera-ture that require future research and offer suggestions for howapparent inconsistencies might be resolved through biobehav-ioral investigations.

Typical brain development during earlychildhood and links to ToM and EF

Studies of normative brain development can help explicate thenature of the ToM–EF relationship by highlighting the onto-genetic primacy of brain regions or networks known to sup-port these abilities. These studies could therefore help to de-termine whether ToM or EF is necessary for acquiring theother ability. Addressing the directionality of influence couldbe accomplished by showing either that (a) the neuralstructures/circuits supporting one ability precede the other de-velopmentally, and are perhaps structurally or functionallynecessary to develop the other skill (i.e., either the EF→ToM or ToM→EF proposal); (b) the maturation of commonbrain regions/circuits sufficiently drives both abilities (i.e., thestrict ToM↔EF proposal); or (c) common neural structuresare necessary but not sufficient for both ToM and EF devel-opment, which also recruit domain-specific regions (the lean

ToM↔EF proposal). Latter option c does not rule out a direc-tional EF→ToM [or ToM→EF] explanation if, for instance,the regions involved in an EF [or ToM] network feed into aToM [or EF] network (without reciprocal effects). As we shallsee, the existing literature on normal brain growth is not suf-ficiently advanced to disentangle these options directly.Nevertheless, a discussion of normal brain development isimportant to characterize the temporal onset and trajectoriesof neural maturation in regions linked to ToM and EF, andserves to highlight their interconnectedness across childhood.

The protracted maturation of the human brain is among themost intriguing aspects of human development. During fetaldevelopment, cell proliferation, migration, synaptic growth,and dendritic arborization lead to a brain that is about one-third the size of that of a human adult by the time of birthwith continued growth via genetic influence and environmen-tal modification, brain maturation continues well throughoutchildhood and into early adulthood (Toga, Thompson, &Sowell, 2006). However, different tissues, structures, and cir-cuits mature at different rates and follow different patterns(Giedd & Rapoport, 2010). For instance, the seminal workof Huttenlocher (1979) showed that visual cortex has maximalsynapse production by 4 months of age, whereas this peakoccurs at 3 to 4 years in the medial prefrontal cortex, an areaimplicated in both ToM and EF. In general, the first 2 years oflife are characterized by a dynamic interplay of progressiveand regressive neural events, with brain growth to about 80%of adult size (Lenroot & Giedd, 2006). Total brain volumedoubles in the first year, with an additional 15% in the secondyear (Knickmeyer et al., 2008). By age 6, the brain is nearly95% of its peak size, but continued growth in prefrontal andoccipital regions is observed from ages 5 to 11 (Sowell, et al.,2004). Gray matter volumes (i.e., an indirect measure of glia,vasculature, and neurons with dendritic and synaptic process-es) develop regionally, following an inverted U-shaped trajec-tory (i.e., a preadolescent increase followed by apostadolescent decrease; Giedd et al., 1999). Spatiotemporaldevelopmental patterns are evident in white matter (a proxyfor axonal myelination), as well (Deoni et al., 2011), thoughwhite matter growth tends to follow a more linear trajectory(Giedd et al., 1999).

Evidence suggests that the development of brain structurestends to follow a pattern wherein the areas responsible for themost basic functions develop first, followed by those respon-sible for more complex functions. In a longitudinal study ofgray matter development, Gogtay et al. (2004) found that sen-sorimotor cortices, as well as frontal and occipital poles, ma-tured first, followed by areas involved in spatial orientationand language (i.e., parietal regions), and then those related tomore advanced executive/mental reasoning abilities (i.e., fron-tal lobe). Within the frontal lobe, the prefrontal cortex was thelast to develop. Thus, the brain areas linked to motor andsensory function matured first, followed by areas involved in

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spatial orientation, speech and language development, andattention. Last to mature were areas involved in executivefunction and motor coordination. Notably, the superior tem-poral cortex, which is similar to the prefrontal and inferiorparietal cortices in its role of integrating primary functions,was the last to mature. This is interesting given the importanceof superior temporal regions in ToM (Apperly, Samson,Chiavarino, & Humphreys, 2004). Furthermore, studies usingtensor maps of neural growth have shown that the fastestgrowth rates from 3–6 years of age occur in frontal networkssupporting mental vigilance and goal-directed behavior(Thompson et al., 2000), consistent with PET evidence show-ing that rates of glucose metabolism in frontal cortex doublebetween the ages of 2–4 years (Chugani, Phelps, &Mazziotta,1987). These results are fascinating given that both ToM andEF undergo rapid development during this time (Wellman,2002; Zelazo et al., 2003) and both are widely linked to pre-frontal functioning (discussed in detail below).

Despite the coincident onset of increased proficiency inToM and EF alongside neural maturation, a strict mappingof cortical development onto cognitive functions remainshighly tenuous (Crone & Ridderinkhof, 2011). That is, evenif it is shown that the structures typically associated with EFprecede those related to ToM (or vise versa), our conclusionswould still be limited without a precise mapping of brain de-velopment onto cognition or behavior within the same sample.Without measures of neural activity and EF and ToM, wemust rely on cross-study comparisons and reverse inference(Poldrack, 2011) to explore the developmental primacy of EFor ToM. An ideal example of a within-subjects design thatmapped brain activity onto cognition is by Shaw et al.(2006), who showed that synaptogenic trajectories of corticaldevelopment in prefrontal-specific regions predicted IQ func-tioning in childhood. That both ToM (Baker, Peterson, Pulos,& Kirkland, 2014) and EF (Brydges, Reid, Fox, & Anderson,2012) are associated with IQ provides some indirect evidencethat dynamic neural events in prefrontal regions over earlychildhood may support the development of these cognitiveskills. However, the relationship between ToM and EF cannotbe explained strictly by individual differences in IQ (Carlsonet al., 2002). Thus, in addition to domain-general cognitivefunctions and their associated brain regions, discrete prefron-tal and nonprefrontal regions may be involved in the networkssupporting ToM and EF development.

It is now widely accepted that the brain is organized intofunctional networks, with coordinated activity from multipleregions that support the execution of cognition that drivesbehavior (Grayson & Fair, 2017). Examining functional net-works at rest—Bresting-state networks^ (RSNs)—is usefulbecause this does not require explicit cognitive or behavioraltasks, which for young children are performatively challeng-ing and frequently fraught with error. Rather, RSNs make useof the concept that Bneurons that fire together wire together,^

and thus index the temporal correlation of blood-oxygen-leveldependent (BOLD) signals across brain regions. These pat-terns of synchronized activity during the resting state are con-sidered intrinsic features of brain function, given that theyclosely map onto network architecture during task perfor-mance (Cole, Bassett, Power, Braver, & Petersen, 2014; butsee Davis, Stanley, Moscovitch, & Cabeza, 2017). The mod-ularity of the human brain suggests that it is organized intoBcommunities^ or modules that are highly reproducible (Yeoet al., 2011). In children, these networks include primary sen-sorimotor and visual networks that are segregated andnondistributed; the Bdefault-mode network^ (DMN), whichcomprises the medial prefrontal cortex (mPFC), posterior cin-gulate (PCC)/precuneus, inferior parietal lobule (IPL; includ-ing the angular gyrus), and medial temporal gyrus (MTG); theBdorsal attention network^ which involves the intraparietalsulcus (IPS) and middle temporal cortex; the Bsaliencenetwork^ which includes the dorsal anterior cingulate cortex(dACC) and anterior insula; the Bfrontoparietal network^which includes the dorsolateral PFC (dlPFC), ventrolateralPFC (vlPFC), and dorsomedial PFC (dmPFC); and thelanguage/auditory network.

Critical to the discussion of ToM and EF, the DMN hasbeen consistently linked to ToM in adults (Schilbach,Eickhoff, Rotarska-Jagiela, Fink, & Vogeley, 2008; Spreng& Grady, 2010). It has also been suggested that maturationof both structural and functional connectivity between DMNregions (especially mPFC and PCC) may support social–cog-nitive development over childhood (Supekar et al., 2010; seealso Mak et al., 2017). Distinct developmental trajectories ofspecific DMN nodes have also been reported in 3- to 5-year-old children, with stronger interactions between nodes overthis period (Xiao, Zhai, Friederici, & Jia, 2016). This is con-gruent with the rapid evolution of ToM during this period.Moreover, perturbations in intrinsic connectivity have beenobserved in conditions such as autism, for which ToM isgrossly impaired (see Hull, Jacokes, Torgerson, Irimia, &Van Horn, 2016). Aberrations in connectivity between DMNregions are also demonstrable in children with conduct disor-ders and attention-deficit hyperactivity disorder (ADHD)(Broulidakis et al., 2016), suggesting that alterations inDMN function may be one source of risk for neurocognitiveand neurodevelopmental problems early in life.

In contrast to the DMN, the salience network hassometimes been referred to as the Bexecutive network^using common parceling techniques (Kemmer, Guo,Wang, & Pagnoni, 2015), whereas others have indicatedthat the frontoparietal network is the center of executivecontrol (Seeley et al., 2007; Vincent, Kahn, Snyder,Raichle, & Buckner, 2008). Both of these networks mayexercise distinct Bcontrol^ functions during goal-directedbehavior (Elton & Gao, 2014). Indeed, the developmentof these networks from childhood to adulthood has been

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posited to entail both decreased short-range connectivityand increased long-range connectivity of the nodes thatcompose them (Fair et al., 2007). As with the DMN,structural and functional maturation of these networksover the life course has been suggested to underlie thecapacity for attentional and cognitive control (Uddin,Supekar, Ryali, & Menon, 2011), with deficits in func-tional connectivity apparent in children, adolescents, andadults with ADHD (Castellanos & Proal, 2012; Konrad &Eickhoff, 2010). Interestingly, specific brain regions with-in the frontoparietal and DMN networks show increasedlocal and global functional features from ages 2–6, withresearchers positing that this maturation supports abilitiessuch as ToM, EF, and language (Long, Benischek, Dewey,& Lebel, 2017). These developments continue over thetransition to adolescence (Sherman et al., 2014) and mayexplain the magnitude of individual differences in ToMand EF beyond childhood (Blakemore & Choudhury,2006; Dumontheil, Apperly, & Blakemore, 2010).

Interrogating functional network maturation very early indevelopment (i.e., within the first 2 years of life) gives clues asto the ontogenetic primacy of ToM and EF, which informsinferences about the nature of the ToM–EF relationship. Gaoet al. (2009) have provided remarkable evidence for the estab-lishment and synchronization of brain regions related to ToMand EF in infants from age 2 weeks to 2 years. They demon-strated that, whereas 2-week-old infants show a rudimentaryand incomplete DMN, significant connections are establishedover the first 2 years, with a near-adult-like DMN observed byage 2. Growth in long-range neural connections and globalefficiency over the first 2 years of life across DMN areas hasbeen suggested to underpin the development of social–cogni-tive proficiencies (Gao et al., 2011). In a separate investiga-tion, similar patterns of network synchronization over the first2 years were observed for the dorsal attention network (Gaoet al., 2013). Recently, the growth trajectories of nine func-tional networks were examined (Gao, Alcauter, Smith,Gilmore, & Lin, 2015). Among these were the DMN, sa-lience, frontoparietal, dorsal attention (lateral visual/parietal),and language/auditory networks. The results showed that,across the various networks, the language/auditory and dorsalattention networks matured faster than the DMN, which ma-tured faster than both the frontoparietal and salience networks.Integration between the frontoparietal and DMN networksincreased over the first 2 years, while connectivity betweenthe DMN and salience networks decreased. These resultspoint to discrete, early-emerging cortical networks that governinternal mentalization and executive control, with the possi-bility of cross-talk between specific networks. The progres-sive interaction between DMN and frontoparietal networksover the first 2 years of life may therefore lay the foundationfor the robust associations observed between ToM and EF inearly childhood. Perhaps most striking, these findings support

the notion that the ToM-related functions associated with theDMN may serve as a foundation on which other higher-orderprocesses develop, providing the strongest support yet for theToM→EF hypothesis using RSNmethods. The enduring pos-itive correlation between frontoparietal and DMN networks in6-year-old children (Emerson, Short, Lin, Gilmore, & Gao,2015) is consistent with behavioral evidence of significantcorrelations between ToM and EF in middle childhood(Devine, White, Ensor, & Hughes, 2016). Moreover, in-creased connectivity of both the auditory/language and dorsalattention networks with the frontoparietal network over thefirst 2 years (Gao et al., 2015) is suggestive that these early-emerging networks may developmentally precede and func-tionally modulate activity in the later-maturing networks thatsupport higher-order cognition (a possibility we explore inmore detail below).

Unfortunately, comprehensive longitudinal studies thatsimultaneously assess ToM and EF and their associatedbrain regions—including regionally specific activation,trajectories of white and gray matter change, and func-tional connectivity across regions—have not yet beenconducted. Notwithstanding the immense progress madein understanding both cognitive and neural development,imaging studies have yet to unambiguously elucidate thetemporal emergence of ToM and EF with respect to rep-resentation in the brain. That is, despite the observed de-velopmental precedence of ToM-related networks (DMN)over EF-related networks (frontoparietal and salience)using RSN methods, existing studies of typical brain de-velopment cannot definitely speak to the directionality ofthe ToM–EF relationship on the basis of structural/functional primacy (i.e., ToM→EF or EF→ToM) or theirreliance on common-developing structures/networks (i.e.,ToM↔EF), owing to a lack of longitudinal designs thatexplicitly map cognition onto neural development. A re-cent study by Eggebrecht et al. (2017) is a notable exem-plar of how measures of resting-state functional connec-tivity can be augmented to include measures of behavior/cognition in order to explain the emergence of particularabilities. In their study of infant joint attention from 12 to24 months, brain–behavior associations emerged betweenthe visual and dorsal attention networks and between thevisual and default mode networks (in particular the PCC),suggesting that interactions between these networks maysupport the development of joint attention. This is fasci-nating given the importance of early joint attention forlater ToM ability (Adolphs, 2003). Future studies that le-verage this approach by integrating measures of brain andToM/EF across childhood will be critical to improving ourunderstanding of how such networks support these abili-ties and how intra- and internetwork dynamics explain theunfolding relationship between ToM and EF overdevelopment.

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Neurological disorders as clues to the ToM–EFassociation

Studies of children with neurodevelopmental disorders mayfurther help clarify which theoretical account of the relationbetween ToM and EF is most plausible. The proposal that EFis a prerequisite for ToM (EF→ToM) demands that, in thepresence of EF deficits, there necessarily are ToM deficits aswell. However, children with Prader–Willi and Williams syn-dromes readily pass ToM tasks, even when EF performance isvariable or impaired (Perner & Lang, 2000; Tager-Flusberg,Sullivan, & Boshart, 1997). Similar results have been found inchildren with ADHD (Perner, Kain, & Barchfeld, 2002).Furthermore, ToM deficits (difficulties understanding unreal-ized goals, false belief, pretense, and intention) in neurofibro-matosis type 1 (NF1) cannot be explained by parent-ratedexecutive dysfunction alone (Payne, Porter, Pride, & North,2016). This appears to contradict the directional EF→ToMargument. In contrast, the proposal that ToM is required forEF (ToM →EF) prohibits the existence of intact EF in thepresence of impaired ToM. However, children with autismhave been shown to have intact EF (planning, set-shifting,and inhibition) while exhibiting pronounced deficits in falsebelief understanding (Pellicano, 2007). Also, interventionstudies of children with autism show that training EF has theeffect of improving ToM at follow-up, whereas training ToMdoes not improve EF (Fisher & Happe, 2005). These studiesdiscount the plausibility of the ToM→EF argument. Morecommonly, concomitant deficits in both ToM and EF are ob-served for neurodevelopmental disorders such as autism(Gökçen, Frederickson, & Petrides, 2016; Joseph, 2004;Ozonoff, et al., 1991) and ADHD (Fahie & Symons, 2003;Uekermann, et al., 2010). Although such studies support theToM↔EF argument, they fail to rule out a directional associ-ation, because the assessment of ToM and EF is usually con-current, with no prediction of cognitive decline over time.Thus, contemporaneous ToM and EF impairments could beexplained by impairment in one domain that exerts a down-stream effect on the other, or by a theory that posits a sharedneural network that mutually supports both abilities. It is alsoplausible that the EF deficits previously observed in childrenwith autism are attributable to difficulties understanding theexperimenter’s implicit expectations for the task (White,2013). In such circumstances, purported problems with EFmay actually be born of mentalization problems rather thanprimary executive dysfunction, thereby highlighting the needto closely consider sources of task and instructional varianceto ToM and EF pe r fo rmance in ch i l d r en wi thneurodevelopmental disorders.

Similar discrepancies have been observed in neurodegen-erative diseases. For instance, low ToM at baseline, as mea-sured by the Reading the Mind in the Eyes Test (RMET), maybe a risk for impaired prefrontal/executive functioning and

frontotemporal dementia 2 years later, supporting theToM→EF link (Pardini et al., 2013). Alternatively, in patientswith Alzheimer’s disease, EF impairments contribute to thedeterioration of second-order false belief understanding(Laisney et al., 2013). However, the latter results were corre-lational and therefore do not offer strong support for a direc-tional EF→ToM claim. The relationship between ToM and EFhas also been demonstrated in multiple sclerosis (Henry et al.,2009; Kraemer et al., 2013) and Parkinson’s disease (R. J.Anderson, Simpson, Channon, Samuel, & Brown, 2013;Costa et al., 2013). These studies have used a variety ofmethods to assess ToM, including the RMET, interpretinghuman action from written scenarios, or inferring mentalstates such as the false beliefs of characters in videos. EFhas also been assessed using a variety of tasks indexing re-sponse inhibition, working memory, verbal fluency, and cog-nitive flexibility. Thus, broadband EF deficits appear to corre-late with broadband ToM deficits in these populations, thoughit is unclear whether particular aspects of EF are more stronglyrelated to specific ToM-related abilities. Finally, evidencefrom studies of adults with acquired neurological patholo-gy—subcortical pathologies, cortical degenerative disorders,frontal focal lesions, traumatic brain injury, and epilepsy—shows that, across a host of classical ToM tasks and EF do-mains (updating, shifting, inhibition, and access), congruentimpairments in ToM and EF are present in 64% of cases (seeAboulafia-Brakha, Christe, Martory, & Annoni, 2011, for areview). In a small fraction of samples, ToM and EF werejointly preserved. Perhaps most interestingly, in 16% of cases,EF was impaired while ToM was intact, whereas in 13% ofcases, ToM was impaired while EF was preserved. The factthat these patients could demonstrate, on the one hand, mutu-ally impaired or preserved functioning in ToM and EF or, onthe other, relative sparing of one ability and deficiency in theother, allows for any of the three proposals: ToM→EF, EF→ToM, or ToM↔EF. Indeed, a more nuanced approach thatidentifies the precise neural mechanisms underlying these pa-thologies might prove useful in revealing the conditions underwhich directional or reciprocal relations between ToM and EFemerge.

Studies of children with neurological disorders or acquiredbrain injury are also informative. For instance, children withtraumatic brain injury (TBI) show both broad ToM and EFdeficits (Robinson et al., 2014). Moreover, Dennis et al.(2013) examined how injury to specific brain networks wasassociated with different aspects of ToM. Damage to the cen-tral executive network (involving the dlPFC, posterior parietalcortices, and subcortical regions) was related to conative ToM(i.e., the ability to understand how acts like empathic praise orironic criticism can influence another person’s thoughts orfeelings), suggesting that ToM expression may depend onaspects of EF such as cognitive inhibition (see also Dennis,Agostino, Roncadin, & Levin, 2009). However, disruptions to

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other networks, such as the DMN and mirror neuron/empathynetwork, were also related to ToM, suggesting that EF deficitsdo not fully account for all ToM impairments in childhoodTBI. More recently, Ryan et al. (2017) examined the contri-bution of large-scale neural networks to cognitive, affective,and conative ToM deficits in a large sample (N = 137) oftypically developing children with mild to severe TBI. Theydemonstrated volumetric reductions in several large-scale net-works that support ToM, including the DMN, salience, andcentral executive networks, as well as two additional networksspecific to social cognition—the cerebro-cerebellarmentalizing network and the mirror-neuron empathy network.Of note, the parcellation approach used in these studies dif-fered from that of the RSN studies noted above, making com-parisons difficult. However, when Ryan et al. (2017) exam-ined specific nodes within these networks, they found thatpoor cognitive ToM was associated with gray matter reduc-tions in the temporo-parietal junction (TPJ), superior temporalsulcus (STS), and cerebellum; poor conative ToM was asso-ciated with reduced volume of the premotor area, IPL, andinferior frontal gyrus (IFG); and poor emotional ToM wasassociated with reduced amygdala volume. As we will seebelow, these findings overlap with those from task-based neu-roimaging studies and converge on the conclusion that keyneural nodes that participate in complex networks may pro-vide a substrate for the co-development of ToM and EF.

Concurrent impairments in ToM and EF have also beenobserved in children with cardiac malformations (TGA;Calderon et al., 2010), cerebral palsy (Caillies, Hody, &Calmus, 2012), and focal epilepsy (Giovagnoli et al. 2011).Importantly, although many of these studies suggested thatdeficits in ToM may be the result of executive dysfunction,such conclusions are often predicated on assumptionsconcerning the role of EF in online social reasoning (i.e., apresumed EF→ToM relation). Although not implausible,these proposals require an explicit examination of the predic-tive roles of ToM and EF in each other’s development. Aminimal requirement for making directional assertions is totest both reciprocal effects after controlling for key confounds,and a more stringent requirement is to assess both ToM andEF at various time points and examine their cross-lagged lon-gitudinal effects. Including measures of ToM and EF at thetime of or shortly after the brain insult and having premorbidlevels of functioning would further enable causal inferences tobe drawn. Currently, such approaches are rarely if ever feasi-ble in clinical studies of this kind, and usually for sensiblereasons: lack of appropriate measurements, unpredictable ill-ness onset, and priority of providing acute care. The fallout isa lack of clarity regarding the directionality of the ToM–EFrelationship in either normative or patient samples. However,the advent of reliable and valid neuropsychological assess-ment tools capable of being delivered at bedside in settingssuch as the emergency department (Khetani, Brooks,

Mikrogianakis, & Barlow, 2016) offers promise for baselineassessment of functioning and outcome monitoring in severalpediatric conditions. Moreover, recent calls for regular screen-ing of ToM in children and adults with varied neurologicalimpairments (Adenzato & Poletti, 2013; Ryan et al., 2015)may promote routine assessment of ToM and EF simulta-neously. In turn, tracking how these abilities unfold in theaftermath of injury/diagnosis may facilitate an examinationof how changes in these abilities predict decline, stagnancy,or recovery in one or the other’s development, thereby offer-ing an avenue for expounding the directionality of the ToM–EF relationship.

In sum, the neurological evidence from pediatric, adult, andgeriatric patients has not yielded consistent findings, in largepart because of the vast heterogeneity in the quality, degree ofdeficit, and functional relations between ToM and EF acrossconditions. These studies do not enable unambiguous conclu-sions regarding the functional dependence of ToM and EF,and all three theories (ToM→EF, EF→ToM, or ToM↔EF)remain tenable on the basis of research in these areas.

Brain lesion studies

Studies from patients with brain lesions may shed further lighton the nature of the ToM–EF relation. In these studies, thepresence of a particular lesion (X) and associated cognitivedeficit in one domain (Y) but sparing in another domain (Z)suggests that: (1) area X is necessary for Y, (2) area X isneither necessary nor sufficient for Z, and (3) function Y isnot important for function Z. If region X is associated withimpairment in Y and Z, then X may subserve both functions,or it may subserve one function that in turn impacts the otherin a directional manner. Studies documenting mutual impair-ments in Y and Z as a function of lesion X may thereforesupport either directional or shared accounts of association.As we shall see below, this lack of clarity hampers conclusionsregarding the nature of the ToM–EF relationship in neuropsy-chological and brain lesion studies.

In an early study of 31 patients with right or left frontallesions, deficits in both ToM (first- and second-order falsebelief understanding) and a broad set of EFs were observed,relative to healthy controls (Rowe, Bullock, Polkey, &Morris,2001). However, the results indicated that ToM deficits couldnot be explained by executive dysfunction. The fact that bothToM and EF were impaired, without a clear EF→ToM link,best fits a ToM↔EF model, but it does not rule out a ToM→EF effect. Unfortunately, the researchers did not localize thespecific frontal regions involved in mental state attribution,making it difficult to understand which areas werededicated to ToM and/or EF. Another early study by Fine,Lumsden, and Blair (2001) showed that patient B.M., suffer-ing from congenital left amygdala damage, had profoundly

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impaired mental state representation in adulthood but showedrelative sparing of EF (inhibition, goal-directed behavior, andsequencing). Damage to the amygdala either congenitally orin early childhood may be particularly detrimental to ToM,as damage in adulthood (e.g., as part of an anterior temporallobectomy) is less predictive of ToM problems (Shaw et al.,2004). Similar findings of separable neural contributions toToM and EFwere found in a case of frontotemporal dementia,where patient J.M. showed severely impaired ToM (first- andsecond-order false beliefs, and faux pas) but intact EF on theWisconsin Card Sort Test, which is generally considered a testof set shifting (Lough, Gregory, & Hodges, 2001). These re-sults support a lean version of the EF→ToM proposal (i.e., EFmay facilitate ToM but is not sufficient for it; otherwise, ToMwould also be intact). Perhaps more conclusively, these resultssuggest that discrete rather than completely overlapping brainregions are involved in ToM and EF, with the sparing of oneability but not the other being at odds with a strict ToM↔EFrelational model.

Many neuropsychological patient studies now suggestmore specific neural contributions to ToM and EF. For in-stance, patients with bilateral vlPFC/orbitofrontal (OFC) le-sions demonstrate subtle impairments in social reasoning (i.e.,in understanding faux pas, but not first- or second-order falsebeliefs) akin to those found in high-functioning autism,whereas damage to left dlPFC is associated with workingmemory but not ToM deficits (Stone, Baron-Cohen, &Knight, 1998). Recent evidence has suggested that affectivecomponents of ToM may be subserved by ventromedial pre-frontal cortex (vmPFC), whereas dorsolateral regions maysupport cognitive aspects of ToM (Kalbe et al., 2010;Leopold et al., 2012; Shamay-Tsoory & Aharon-Peretz,2007; Shamay-Tsoory, Tomer, Berger, Goldsher, & Aharon-Peretz, 2005; Stuss, Gallup, & Alexander, 2001).Interestingly, the dlPFC is widely implicated in EF (Alvarez& Emory, 2006; Stuss, 2011). Moreover, ToM deficits in pa-tients with prefrontal cortical lesions have been shown to belargely attributable to problems with EF, such as workingmemory, shifting, and inhibition, while deficits in false beliefreasoning among patients with damage to the TPJ are inde-pendent of EF (Apperly et al., 2004). Involvement of the TPJin spontaneous belief inference has recently been demonstrat-ed in two patients with highly localized lesions in the leftposterior part of the TPJ (Biervoye, Dricot, Ivanoiu, &Samson, 2016). With regard to to the relationship betweenToM and EF, it may be that ventromedial or posteriortemporo-parietal regions are specifically involved in the rep-resentation of mental states, whereas dorsolateral regions sup-port the domain-general executive processes needed to suc-cessfully manage and functionally apply those representations(i.e., inhibiting self-perspectives, holding and manipulating inmemory, shifting reference frames, etc.). This is consistentwith a lean version of the EF→ToM proposal in which EF

may be necessary but not sufficient for ToM processing.However, these results have been challenged by findingsshowing that a patient suffering a rare bilateral anterior cere-bral artery infarction that damaged the mPFC had markedproblems with set shifting and planning but not with ToM(Bird, Castelli, Malik, Frith, & Husain, 2004; see also Bach,Happe, Fleminger, & Powell, 2000). This finding contradictsthe EF→ToM proposal, while allowing the possibility thatToM is necessary, but not sufficient, for EF (the lean ToM→EF proposal).

On balance, the fact that patients with comparable prefron-tal lesions show variable levels of ToM and/or EF perfor-mance may be most consistent with the ToM↔EF proposalof a shared neural network supporting both skills, with otherdiscrete regions separately underlying specific aspects of ToMand EF. The discrepancies across studies, then, may be due toa variety of mitigating factors, such as the recruitment of pa-tients with differing brain pathologies/etiologies, diffuse brainlesions that fail to localize and may involve neighboring re-gions, and variability in the selection of ToM and EF tasks.For instance, it may be that the unspecified effects of particularlesions on ToM and EF reflect a more scrupulous phenome-non that is not adequately captured in all studies, such as thepossibility that EF accounts for deficits in the cognitive but notthe emotional dimension of ToM reasoning (see Yeh, Tsai,Tsai, Lo, & Wang, 2017, for an example).

Several issues remain to be addressed in future research.Issues with lesion localization and sample heterogeneity (e.g.,patients with either congenital or acquired neurological pa-thology) clearly have a bearing on the reliability of the find-ings across studies. Another obstacle in addressing questionsregarding the directionality of the ToM—EF relationship isthe temporal cascading of effects. For instance, preservationof EF with impaired ToM allows for the possibility of EF→ToM, just as preservation of ToMwith impaired EF allows forthe ToM→EF proposal. However, studies that compare thepreservation of EF and ToM do not directly address whetherToM or EF is dependent on the other. Indeed, such dissocia-tions are necessary, but not sufficient, in order to make infer-ences about causality. Future studies might address thesequestions more directly by longitudinally tracking patientswith lesions to specific neural regions/networks involved inToM and EF and examining the resultant impact (deteriorationor preservation) on the other ability over time.

Task-based neuroimaging studies of ToMand EF

Above we described several findings on RSNs, their matura-tion, and their putative relation to ToM and EF. It has beenargued, however, that a full appreciation of the brain basis ofcognition requires an examination of the networks that are

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activatedwhile performing cognitive tasks (rather than at rest).Indeed, it is not always the case that RSNs neatly dovetail withtask-based network activity (see Campbell & Schacter, 2017).In contrast to RSNs, the neural networks activated duringtasks have been called Bcognitive function networks^(CFNs; Davis et al., 2017). Like RSNs, CFNs comprise dis-crete brain regions that form integrated networks supportingparticular cognitive abilities. Davis and colleagues describedseveral challenges with relying on RSNs alone to understandthe neural basis of cognition: (1) the brain regions connectedwithin RSNs may be dissociable in a CFN (the dissociationproblem); (2) regions belonging to different RSNs may co-activate in a CFN (the association problem); (3) a single brainregion in an RSN may ostensibly participate in more than oneCFN (the versatility problem); and (4) the extent to which abrain region is connected to other structures within an RSNdoes not presage its importance in a CFN (the performancespecificity problem). These points underscore the importanceof examining the neural structures that are specifically activat-ed during ToM and EF tasks, which provides a complemen-tary approach to RSN methods of elucidating the nature of theToM–EF relation.

Rapid improvements in the quality and accessibility oftools for assessing brain structure and function over the last20 years have led to an unprecedented number of studies onthe neural foundations of ToM and EF. Common approachesinclude the use of electroencephalography (EEG; and its as-sociated event-related potentials, ERPs), structural magneticresonance imaging (MRI; and its functional subtype, fMRI),diffusion imaging (dMRI or DTI), and functional near-infrared spectroscopy (fNIRS). In this section, we review theextensive evidence on CFNs and their participant regions inrelation to ToM and EF.

Theory of mind findings

In the adult literature, neuroimaging studies have revealed a re-markably consistent set of brain regions recruited during ToMtasks: the bilateral TPJ (the inferior parietal lobule at the junctionwith the posterior temporal cortex), the mPFC (including the an-terior paracingulate cortex), the precuneus/PCC, and the STS/MTG (Amodio & Frith, 2006; Decety & Sommerville, 2003;Gallagher & Frith, 2003; Gallagher et al., 2000; Ruby & Decety,2003; Saxe & Kanwisher, 2003; Saxe, Whitfield-Gabrieli,Scholz, & Pelphrey, 2009; Völlm, et al., 2006). Meta-analyticstudies have corroborated the notion of a distributed fronto-temporo-parietal CFN that supports the ability to impute others’goals, desires, intentions, and beliefs (Molenberghs, Johnson,Henry, & Mattingley, 2016; Schurz, Radua, Aichhorn, Richlan,& Perner, 2014; Van Overwalle, 2009).

In children, early EEG studies demonstrated that restingEEG alpha activity localized to the dmPFC and TPJ was pos-itively associated with 4-year-olds’ representational ToM,

even after controlling for EF (e.g., inhibitory control andshifting; Sabbagh, Bowman, Evraire, & Ito, 2009). These re-sults indicate that EF cannot account for the pattern of brainactivity that accompanies ToM reasoning, and instead suggesta dedicated neural circuit for ToM. ERP studies comparingadults and 4- to 6-year-old children have revealed comparableprefrontal activity in those who can effectively reason aboutmental states (Liu, Sabbagh, Gehring, & Wellman, 2009),signifying a critical role of the PFC in ToM deployment anddevelopment (see also Meinhardt, Kühn-Popp, Sommer, &Sodian, 2012). Using ERP methods, it has also been shownthat both belief and desire reasoning are associated withmidfrontal scalp activations, whereas belief reasoning showsan additional selective right-posterior scalp distribution(Bowman, Liu, Meltzoff, & Wellman, 2012). These resultsalign with the idea that early desire reasoning may help toscaffold later belief understanding, consistent with behavioralstudies that emphasize a developmental progression in ToM-based skills (see Wellman, Fang, & Peterson, 2011). On thebasis of these EEG/ERP studies, it does not appear that thestrict ToM↔EF proposal of a wholly overlapping neural basisfor ToM and EF is tenable. However, definitive conclusionsare difficult to draw, given the limited spatial resolution ofEEG/ERP measures. As a result, neuroimaging methods withimproved spatial resolution offer an important window intothe neural basis of ToM in children.

Imaging studies in children, though rare as compared towith adults, are supportive of the CFN described above in-volving the TPJ, mPFC, PCC/precuneus, and STS/MTG fromage 6 to 12 (Kobayashi, Glover, & Temple, 2007; Saxe et al.,2009; Sommer et al., 2010). Using fMRI, Gweon, Dodell-Feder, Bedny, and Saxe (2012) showed increasing activationin the bilateral TPJ from age 5 to 11, suggesting progressiveselectivity of this region in reasoning about mental states.Moreover, Wiesmann, Schreiber, Singer, Steinbeis, andFriederici (2017) recently used diffusion-weighted MRI toshow that breakthroughs in false belief understanding fromage 3 to 4 are associated with age-related changes in localwhite matter structure in the TPJ, mPFC, precuneus, andMTG. As with prior EEG findings, these changes were inde-pendent of EF and language abilities, suggesting a dedicatedneural circuit underlying advances in ToM from age 3 to 4.Wiesmann and colleagues also demonstrated increased con-nectivity between temporoparietal and IFG regions in relationto ToM performance, suggesting both white matter maturationand increased connectivity strength across these classic ToMregions in preschool-aged children. Moreover, the progressionfrom desire to belief reasoning being supported by the TPJ hasrecently been replicated using fNIRS methods (Bowman,Kovelman, Hu, & Wellman, 2015). On aggregate, these find-ings coalesce with electrophysiological evidence in dispellingthe strict version of the ToM↔EF proposal of a completelyoverlapping neural network. Importantly, such findings do not

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rule out the possibility of shared hubs that participate in net-works for both ToM and EF. This first requires a delineation ofthe neural regions involved in EF.

Executive functioning findings

As we described above, EF reflects a constellation of cogni-tive abilities—inhibition, working memory, cognitive flexibil-ity, self-monitoring, and so forth—and any one of these com-ponents could be functionally related to ToM. Many tasksassess EF, but most of them do not effectively separate thesecomponents. For instance, in older teenagers and adults, theWisconsin Card Sorting Test (WCST), which has been sug-gested to involve many EFs (Miyake et al., 2000), has beenshown to activate the dlPFC, vmPFC, and IPL (Alvarez &Emory, 2006), which parallels results from patient lesion stud-ies (Stuss et al., 2000). Response inhibition is strongly asso-ciated with activity in the ACC, dlPFC, superior parietal lob-ule, and vlPFC (Aron, Robbins, & Poldrack, 2004; Wageret al., 2005). Similar areas have been shown to support work-ing memory, with increased co-activation in ACC and IFG inindividuals with larger working memory spans (Osaka et al.,2004). In general, working memory involves dorsolateral,ventrolateral, and anterior prefrontal regions along with pari-etal areas (Veltman, Rombouts, & Dolan, 2003). Responseselection under conditions of high attentional load is furtherassociated with activity in bilateral frontal eye fields andintraparietal sulcus (Culham, Cavanagh, & Kanwisher,2001). Though the degree of activation for each EF dimensionis not reviewed here due to space restrictions, it is clear that anumber of regions appear to be associated with broadband EFabilities. Studies using transcranial magnetic stimulation(TMS) have confirmed these associations (Osaka et al., 2007).

In children, neuroimaging studies are largely in agreementwith the adult literature. For example, in anMRI study of 5- to10-year-old children, Kharitonova, Martin, Gabrieli, andSheridan (2013) showed that age-related improvements incognitive control were associated with gray matter thinningin the ACC and right IFG, whereas changes in working mem-ory were associated with thinning in the superior parietal cor-tex, possibly reflecting a process of selective pruning andincreased myelination over childhood. Developmental chang-es in mPFC have also been associated with cognitive controlin this age group (Sheridan, Kharitonova, Martin, Chatterjee,& Gabrieli, 2014). In a study of 339 participants ages 8 to 89,using both MRI and DTI, it was shown that intracorticalmyelination is associated with intra-individual variability ina speeded inhibition task across the human lifespan, with EFgrowth being observed through the fourth decade of life(Grydeland, Walhovd, Tamnes, Westlye, & Fjell, 2013).Multimodal imaging techniques of this sort have further re-vealed that cortical surface area of the ACC is a critical pre-dictor of cognitive control, with the strongest effects being

observed in young children (Fjell et al., 2012; Velanova,Wheeler, & Luna, 2008; Walhovd et al., 2012). There is alsoevidence for progressive age-related increases in activation inlateral and medial fronto-striatal regions, as well as for thestrength of interregional connectivity during cognitive controltasks (including inhibition and flexibility; see Rubia, 2013, fora review). Together, these findings underscore the importanceof dlPFC, ACC, and temporoparietal maturation in the devel-opment of common EFs in childhood.

Relation between ToM and EF

Meta-analytic findings of brain regions implicated in EF inboth children and adults (Alvarez & Emory, 2006; Houdé,Rossi, Lubin, & Joliot, 2010; Wager, Jonides, & Reading,2004) have identified a number of areas that are frequentlyassociated with ToM; these include the vmPFC (Shamay-Tsoory, Tibi-Elhanany, & Aharon-Peretz, 2006), IPL(Decety & Sommerville, 2003; Uddin, Molnar-Szakacs,Zaidel, & Iacoboni, 2006), anterior insula (especially inunderstanding feeling states; see Lamm & Singer, 2010),and temporoparietal regions (Saxe et al., 2009). The dmPFChas been linked to both ToM and inhibitory control in separatestudies (Dodell-Feder, Koster-Hale, Bedny, & Saxe, 2011;Simmonds, Pekar, &Mostofsky, 2008). Moreover, in additionto its role in ToM, the TPJ has been characterized as an atten-tional Bcircuit breaker,^ enabling the disengagement andreorienting of attention (Corbetta, Patel, & Shulman, 2008).On the surface, these findings may intimate domain-generalproperties of these regions that best fit with the ToM↔EFproposal of a shared neural architecture. However, this is com-plicated by the fact that these comparisons are made acrossstudies, so it is plausible that the observed activity in responseto a given task could be explained by the other (unmeasured)cognitive function being enlisted to perform that task. Thus,within-subjects designs that compare neural activity duringToM and EF tasks are critical. In one example, van derMeer, Groenewold, Nolen, Pijnenborg, and Aleman (2011)showed that a high- versus low-inhibition belief reasoningtask and a basic stop-signal inhibition task both recruitedIFG, whereas ToM alone recruited the STG, MTG, TPJ, andprecuneus. These results suggest a common mechanism forself-perspective inhibition and basic response inhibition, aswell as a non-EF-mediated, ToM-specific neural mechanism.Such findings are consistent with a lean EF→ToM relationallink in which EF is enlisted to support ToM activities thatrequire perspective inhibition. These results also align withbehavioral studies that have demonstrated that ToM perfor-mance varies as a function of working memory demands(Bull, Phillips, & Conway, 2008; McKinnon & Moscovitch,2007) and that the depletion of EF during delay of gratificationstymies otherwise capable 4- and 5-year-olds’ ability to reasonabout mental states (Powell & Carey, 2017). The latter study,

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while convincingly showing that EF depletion reduces ToMperformance, cannot rule out the possibility that ToM deple-tion also reduces EF performance—indeed, no such study hasbeen conducted, to our knowledge. Additionally, such a find-ing may be explained by the idea that something common toboth ToM and EF is depleted during delay of gratification,such as the attentional resources used to compute reward ben-efits or response costs, a theme we will return to at the end ofthis review.

The finding that EF may modulate ToM could be explainedby (1) the Bperformance account,^ in which immature EFplaces limits on children’s ability to effectively represent andreason about mental states during actual task performance, or(2) the Bemergence account,^ in which EF is required in orderto form conceptual and mentalistic representations of others.Saxe, Schulz, and Jiang (2006b) directly addressed this ques-tion using fMRI in a sample of adults by conducting a series ofexperiments using false belief (ToM) and algorithm (EF)tasks, which both required response selection and applicationto the same stimulus materials (thus matching the task de-mands). They found common neural activity in mPFC, bilat-eral parietal sulcus, ACC, and left TPJ. The right TPJ was onlyassociatedwith false belief performance. These results suggestthat ToM reasoning recruits brain regions associated with re-sponse selection, inhibition, and attention, as well as regionsthat are specifically required in order to represent the contentsof others’ thoughts, including the TPJ and, perhaps moreweakly, the mPFC and PCC. Since EF was important forToM in this sample of adults, the results favored theBperformance^ over the Bemergence^ account of the EF→ToM relationship. That is, even if ToM tasks involve execu-tive demands, mental-state reasoning is subserved by a dis-tinct neural substrate. The authors further suggested that theirresults stood in opposition to a strict ToM↔EF account, inwhich ToM and EF are associated because they rely on thesame neural network. Similar results were subsequently dem-onstrated in 6- to 11-year-old children (Saxe et al., 2009).

Another study examining ToM and EF in the same sampleused nonverbal visual tasks for false belief understanding andinhibitory control that were virtually identical (Rothmayret al., 2011). The ToM and EF tasks showed substantial over-lap of activity not only in right TPJ, but also in dmPFC, thedorsal part of the left TPJ, and lateral prefrontal regions (areasalso linked to memory; Cabeza & Nyberg, 2000). These find-ings suggest that the mPFC and TPJ are not specific to eithercognitive ability. Furthermore, the authors suggested thatthese regions may support domain-general processes in-volved in both ToM and EF, explicitly favoring theToM↔EF proposal. However, the recruitment of indepen-dent regions for both ToM and EF suggests that, if there isa shared network for ToM and EF, the areas recruited bythe different capacities are not completely overlapping(lean ToM↔EF relation).

Common hubs for ToM and EF?

The notion that ToM and EF recruit common neural regionsunderscores the versatility problem described by Davis et al.(2017) above—that is, specific brain regions may participatein more than one CFN in the service of different cognitivetasks. One explanation for the seeming overlap between thebrain regions involved in ToM and EF is that these regionsoperate as hubs within distributed neural networks that sup-port the development of both abilities. This may partially ex-plain why these abilities are modestly but robustly correlatedacross childhood. Indeed, data from both structural and func-tional brain analyses have revealed several cortical hubs thatare both densely anatomically connected and dynamically in-teractive (see M. P. van den Heuvel & Sporns, 2013, for areview). Structural hubs (derived from diffusion imaging) in-clude the precuneus/PCC, ACC, dlPFC, and insular cortex, aswell as MTG/STG. Similarly, functional hubs (derived fromresting-state fMRI) include the precuneus/PCC, ACC,vmPFC, and IPL. These hubs traditionally localize to theDMN or executive control network (see Cole, Pathak, &Schneider, 2010). Perhaps more interesting, certain hub re-gions may participate in more than one network. The ventralpart of the PCC, for instance, shows strong functional connec-tivity to the DMN, whereas regions in the dorsal PCC showhigh connectivity to the frontoparietal network (Leech, Braga,& Sharp, 2012). Such fine-grained distinctions have also beenestablished in the TPJ. For example, Scholz, Triantafyllou,Whitfield-Gabrieli, Brown, and Saxe (2009) used high-resolution imaging to show that, within the right TPJ, thereis a 6- to 10-mm spatial displacement between the activationsfor representational ToM and attentional reorienting. Marset al. (2012) then showed that the TPJ can be structurallydivided into three subregions, each demonstrating differentialfunctional connectivity to brain regions in the default mode,frontoparietal, and salience networks. This degree of distinc-tion may be less pronounced once key task confounds arecontrolled, with an overarching function of the TPJ in additionto some specialization (Özdem, Brass, Van der Cruyssen, &Van Overwalle, 2017). Recent reviews have also pointed tothe IPL as a hub that participates in a broad range of cognitivefunctions, from bottom-up perception to higher-order abilitiessuch as ToM and EF (Igelström & Graziano, 2017). Othershave suggested that some hubs have a heterogeneousquality, participating in different functional networks (Tomasi& Volkow, 2011).

These studies on neural hubs offer a unique opportunity forfuture research to expound the nature of the ToM–EF relation-ship. First, continued use of high-resolution imaging techniquesis critical to fleshing out the degrees of structural/functional specificity for ToM and EF. Paired use of diffusionimaging, to delineate structural connectivity, and fMRI/NIRS,to describe functional properties, will certainly lead to increased

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precision in differentiating among the regions/networks dedi-cated to ToM and EF. Failure to interrogate these regions at adetailed level of analyses may hamper efforts to uncover thestructural and functional specificity of brain regions and theirattendant networks in supporting ToM and EF.

Moreover, quantifying the extent to which certain neuralnetworks/hubs are activated in relation to ToM and EF tasksmay help inform the directionality of the ToM–EF relation-ship. One approach is to map the neural co-activation patternsduring EF and ToM tasks separately within the same partici-pants (i.e., to map their CFNs), and then determine whetherthe covariance pattern elicited from one cognitive ability morestrongly predicts performance in the other ability. Using func-tional connectivity methods, a related approach could be ap-plied in which RSNs are first established using standardresting-state methods and then used to predict both ToM andEF performance outside the scanner (e.g., Kanske, Böckler,Trautwein, & Singer, 2015; Reineberg, Andrews-Hanna,Depue, Friedman, & Banich, 2015). Not only would thismethod validate the differential involvement of RSNs in par-ticular cognitive tasks, it would enable an assessment ofwhether the RSNs conventionally assigned to one set of abil-ities (executive control vs. internal mentalization) morestrongly predict performance in the other cognitive domain.Do both DMN and frontoparietal activity independently pre-dict ToM, but only frontoparietal activity predicts EF? Thismay provide RSN evidence of a directional EF→ToM rela-tionship. In addition, this method would complement the lit-erature examining the interaction between RSNs in supportingparticular abilities; that is, it is possible that network interac-tions are stronger for one ability than for the other. Perhaps theDMN and the frontoparietal network (or hubs within them)interact more strongly during ToM than during EF. Such afinding would suggest that EF modules are required for ToMto a greater extent than the reverse, again underlining an EF→ToM directional relationship. As an example, it has beenshown that increased cooperation between the DMN andfrontoparietal regions is associated with more rapid memoryrecollection (Fornito, Harrison, Zalesky, & Simons, 2012),with the PCC acting as a connectivity hub facilitating efficientprocessing. This sort of analysis is suggestive that the tradi-tionally prescribed, and sometimes competing, brain regions/networks may have heterogeneous and integrative functions(Allen et al., 2014; Cocchi, Zalesky, Fornito, & Mattingley,2013; Power, Schlaggar, Lessov-Schlaggar, & Petersen,2013). At a whole-brain level, examining how connectedfrontoparietal, salience, and DMN regions are to the rest ofthe brain may inform regarding the extent to whichmentalization versus executive control modulates othercognitive functions. Reineberg and Banich (2016) recentlyshowed that nodes both within and outside the frontparietalnetwork are associated with individual differences in commonEFs. They also identified potential hubs, including the

precuneus, inferior temporal gyrus, and frontal pole—the lat-ter of which was proposed to support cognitive representationof actions and plans. Should this cortical hub, which involvesa gradient for representing cognitive and emotional states,emerge in future studies as being associating with EF, thismight provide evidence that representing mental states sup-ports EF (ToM→EF). More generally, discovering how con-nected particular nodes/hubs are to the rest of the brain willhelp determine how accessible other regions are to higher-level modulation by either representation/reflection (ToM) orcontrol (EF), thereby expounding the relative influences ofToM and EF on each other, and on other cognitive abilities.Complementary use of methods to assess structural connec-tivity and white matter tract integrity across regions will alsoimprove our understanding of how particular brain regions/hubs work together in supporting ToM and EF, and the degreeto which their association is due to common versus disparatemechanisms, or reciprocal versus directional influence.

Summary, limitations, and future directions

The present review drew on evidence from cognitive neuro-science to examine and help explain the developmental rela-tion between ToM and EF. Three theories to explain this as-sociation are that (1) ToM relies on EF (EF→ToM), (2) EFrelies on ToM (ToM→EF), and (3) ToM and EF are relatedthrough a shared neural system that supports both abilities(ToM↔EF). The key findings from this review are that (1)behavioral measures of ToM and EF are indeed robustly in-terrelated during childhood, both cross-sectionally and longi-tudinally, with the preponderance of research favoring theEF→ToM relationship over the reverse directional link; (2)evidence from neurodevelopmental, neurodegenerative, andneuropsychological lesion studies provides support for thenotion that ToM and EF are at least partially separable in thebrain, but also demonstrate considerable overlap; (3) studiesof normative brain development support the coincident andrapid maturation of ToM and EF over the first 5 years of life,though few studies have explicitly mapped measures of bothToM and EF onto measures of structural or functional neuraldevelopment within the same sample; (4) functional connec-tivity analysis suggests the possibility that the intrinsic,resting-state networks traditionally associated with ToM maydevelopmentally precede those supporting EF, with increasedintegration between networks over time; (5) studies examin-ing cognitive function networks generally converge on theconclusion that ToM and EF rely on distinct but also sharedneural circuits, particularly in the mPFC, IPL, TJP, and IFG;and (6) certain brain regions may serve as hubs that are bothstructurally and functionally linked to other regions thatBassemble^ together to support both ToMandEF, and such hubsmay support network interactions that explain the correlation

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between ToM and EF over childhood. Future use of RSN, CFN,and structural connectivity methods will help illuminate exactlywhy ToM and EF are associated and the degree to which thesemodulate one another and other cognitive proficiencies over thelife course.

As of this writing, it appears that only the strict version ofthe ToM↔EF hypothesis, in which ToM and EF rely oncompletely overlapping neural structures, can be ruled outwith confidence. However, stringent versions of the direction-al EF→ToM and ToM→EF proposals, in which one of theseabilities is sufficient for the other, also seem unlikely. Rather,it appears that ToM and EF share some overlapping neuralstructures, while also recruiting regions that are specially de-signed for mental representation and executive control, re-spectively. Shared regions, which may operate as neural hubs,could partially explain the robust correlation between ToMand EF across childhood. Moreover, the extent to which thesehubs and other nodes within ToM and EF networks are struc-turally or functionally connected, or the degree to which thenetworks cooperate across tasks, might help explain the exis-tence of directional relations. Future research will be needed todisentangle these possibilities, with continued developmentand use of high-resolution imaging techniques making thisenterprise within reach.

The highly replicable behavioral finding of an EF→ToMlink is suggestive that performance on several ToM tasks in-volves neural mechanisms for response selection, inhibition,attention, and working memory (Saxe, Moran, Scholz, &Gabrieli, 2006a; Saxe et al., 2006b). However, the relativeprofusion of evidence in favor of this directional link may bedue to a lack of empirical inquiry about competing models.Specifically, the ToM→EF proposal has been largely ignoredin the adult literature, perhaps owing to the difficulty of sys-tematically varying the level of mental state reasoning in orderto examine the effects on EF. Twomethodological approachesthat may be useful in this context have been pioneered byApperly and colleagues. The first is to manipulate the degreeof congruence between self and other perspectives in a visualperspective-taking paradigm (see Qureshi, Apperly, &Samson, 2010), and the second is to manipulate psychologi-cally relevant ToM parameters (e.g., true vs. false belief;Hartwright, Apperly, & Hansen, 2012). Using the latter ap-proach, Hartwright et al. showed that variation in the valenceof belief and desire recruits neural regions regularly implicat-ed in ToM (TPJ and mPFC), but also recruits nodes involvedin EF (dmPFC, including dorsal ACC). This finding is com-monly interpreted as EF (e.g., perspective inhibition)supporting ToM (EF→ToM). Indeed, it may be the case thatincreased coupling of DMN and frontoparietal regions is re-quired for goal-directed social cognition (see Igelström &Graziano, 2017). Using these methods, firm directional con-clusions could be enhanced by measuring ToM and EF in thesame study and examining their mediational effects on each

other. For instance, inhibition (measured behaviorally) maymediate the link between observed neural activity in regionssuch as ACC and false belief reasoning (EF→ToM).Alternatively, the heightened activity in the ACC during falsebelief reasoning may reflect a brain state that is primed forexecutive processing. In this case, ToM may mediate ACCactivity on EF (ToM→EF). Future studies that systematicallyvary EF- and ToM-based parameters and examine the effectson performance in the other domain, and that investigate theseeffects at the level of neurobiology, are ripe avenues for de-velopmental and cognitive psychologists hoping to furtherdelineate the influences of EF and ToM on one another’sdevelopment.

Although the discrete brain regions implicated in ToM andEF have been fairly well described, we still know relativelylittle about the structural and functional connectivity andinterregional/network dynamics supporting these abilities.The extent to which ToM and EF nodes feed into networkssupporting the other ability, or the degree to which relativelyseparable networks interact during ToM and EF tasks, is aburgeoning field that will benefit from continued multimodalresearch that integrates across RSN, CFN, and structural con-nectivity approaches. The use of complementary methodssuch as TMS may also be informative. As an example, TMSapplied over the dlPFC has been shown to induce a selectiveeffect on cognitive aspects of ToM (Costa, Torriero, Oliveri, &Caltagirone, 2008; Kalbe et al., 2010), and has been shown toimpair EF in separate studies (Ko et al., 2008; O. A. van denHeuvel, Van Gorsel, Veltman, & Van Der Werf, 2013). Giventhe purported role of dlPFC in both ToM and EF, disruption ofthis nodal structure may simultaneously interfere with thefunctioning of the networks subserving both ToM and EF. IsdlPFC a common neural structure that supports both ToM andEF? Is it a hub that connects various regions underlying bothabilities? Is the effect on ToM explained by disruption in ex-ecutive skills such a perspective inhibition, or is interferencewith mental state representation driving impairments in EF?Future use of within-subjects designs that simultaneouslymeasure ToM and EF using TMS approaches may shed lighton the specific role of this and other structures in the develop-ment of these cognitive abilities.

Another area for future research is to apply sound theoreticalmodels to understand how componential processes may explainthe shared neural basis of ToM and EF. These may be lower-level perceptual and sensory functions (e.g., see Stone &Gerrans, 2006), but may also involve intermediate cognitive(endo)phenotypes. Candidate processes that may account forsuch an overlap are the allocation of attention, processes forcomparing internal predictions to external stimuli, and responsesuppression/selection.Aswe alluded to above regarding networksynchronization during the first 2 years of life, the allocation ofattention may be one process that underlies both EF and ToM(see Corbetta et al., 2008). For EF, the allocation of attentionmay

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be particularly relevant due to the need for monitoring andinterrupting automatic responses in order to provide a behavior-ally appropriate but conflicting response. In that sense, attentionto salient external stimuli that dictate response selection shouldbe considered a key componential process. For ToM, trackingkey events (e.g., type of object, location transfer, or the presenceor absence of a protagonist) or monitoringmultiple simultaneousbeliefs (e.g., true vs. false beliefs) would also place demands onattentional resources. The seminal role of attention in both ToMand EF is plausible on the basis of the abovementioned evidencethat the dorsal attention network develops faster than the net-works typically recognized to underlie ToM and EF, with con-nectivity changes between certain networks over the first 2 yearsof life (Gao et al., 2015). Interestingly, Santiesteban, Kaur, Bird,and Catmur (2017) recently used disruptive TMS over the rightTPJ to show that domain-general attentional processes may me-diate the ability to take another’s visual perspective during self-perspective judgments. Future use of TMS during ToM and EFtasks that vary in their attentional demands may illuminate thedegree to which such attentional processes are important in fa-cilitating ToM and EF performance.

Furthermore, mental processes for comparing internal pre-dictions to external stimuli may be needed for both EF andToM (Decety & Lamm, 2007; Spengler, von Cramon, &Brass, 2009). For executive inhibition, this involves a com-parison between generated expectations and actual externalstimuli that may require internal models to be inhibited,shifted, or otherwise manipulated in order to successfullycomplete an EF task. For ToM, one must compare an internalmental model of what one actually knows to that which isexternally (or subjectively) known by another; that is, one’sown beliefs, desires, emotions, or intentions need to be com-pared to another person’s in order to successfully completeToM tasks. Thus, a shared neural network for ToM and EFmight be partially explained by the recruitment of commonbrain regions that support constituent abilities needed for bothabilities.

Finally, theoretical models posit that three other cognitivefaculties may underlie ToM and EF, and thus may potentiallyexplain their functional overlap. The first is language ability.For ToM, communication systems may foster the internaliza-tion of multiple perspectives that are borne out in social inter-actions, thereby facilitating the representation of others’ men-tal states (Fernyhough, 2008). For EF, language may scaffoldchildren’s ability to control thoughts and behavior by internal-izing words, gestures, or other semiotic cues that have beenused to regulate the child’s behavior, or that the child has usedto influence others’ behavior (Fernyhough, 2010). From thisperspective, language may facilitate the verbal representationand reasoning about mental states required for ToM, as well asthe capacity for verbal self-regulation and self-monitoring thattypifies EF (Müller, Jacques, Brocki, & Zelazo, 2009).Interestingly, language ability is known to be supported by a

neural mechanism involving the TPJ (Binder et al., 1997;Perner & Aichhorn, 2008). Thus, the link between languageand EF/ToM may not be simply task-driven (i.e., high lan-guage demands). Instead, language may play a functional rolein ToM and EF development, and accordingly, the relativelycircumscribed neural circuits supporting language ability mayfeed into the networks that support ToM and EF.

Another basic process that may be shared by ToM and EF,and thus explain their overlap, is self-consciousness or self-awareness. With regard to ToM, an awareness of the objectiv-ity of one’s own body, thoughts, and experiences is a neces-sary precondition to differentiate self from other, thus enablingthe partitioning and ascription of mental states to self andother. For EF, the capacity to control or inhibit thoughts andbehavior relies on the ability to understand that one is capableof exerting this kind of control, thus demanding self-awareness (Lang & Perner, 2002). Indeed, a recent meta-analysis of fMRI studies revealed that self-recognition andfalse belief understanding share overlapping regions in themPFC (van Veluw & Chance, 2014). As we suggestedabove, mPFC may be a nonspecific region supportingboth ToM and EF. Thus, self-conscious awareness maybe another componential process supporting ToM andEF, and may partially explain their neural and behavioraloverlap.

A third and related process that we propose may explain theToM–EF correspondence is secondary representation. Thisprocess precedes the capacity for meta-representation, whichis believed to underlie belief reasoning and ToM, but followsprimary representation, in which children represent the worldin strictly literal terms (Perner, 1991; Whiten & Suddendorf,2001). Secondary representation emerges in the second yearof life, at which point children are believed to be able toconsider multiple mental models simultaneously. In turn, thiscapacity to hold in mind two (possibly conflicting) represen-tations of the world supports a suite of abilities, such as pre-tend play, cooperation, empathy, and joint attention (Moore,2007). The capacity to represent the intentions of oneself andothers may be of considerable importance here (Moore, 2007;Tomasello, 2001). Neuroimaging studies examining second-ary representation are scarce and are often conflated with thenotion of Bmeta-representation.^ However, Critchley, Wiens,Rotshtein, Öhman, and Dolan (2004) suggested that second-ary representation is supported within PFC and the cingulatecortices, with a particularly prominent role of mPFC (see alsoAmodio & Frith, 2006). Self-consciousness and secondaryrepresentation also relate to the concept of agency—the expe-rience of oneself as the generator of thought and action. Withthis level of understanding, children may begin to successfullydifferentiate self from other and, by extension, begin to repre-sent multiple mental representations simultaneously, while al-so understanding the causal effects of mental states on behav-ior. This has clear implications for the reasoning about mental

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states that underlies ToM and the controlling/inhibiting ofcognition that contributes to EF. Notably, the mPFC is crucial-ly involved in agency (David et al., 2006; David, Newen, &Vogeley, 2008), as is the right TPJ (Decety & Lamm, 2007).

To understand the contributions of these componential pro-cesses to ToM and EF development, these domains them-selves require a more nuanced theoretical analysis. For exam-ple, although models of attention are abundant, it is not clearwhich dimension(s) of attention may be especially involved inToM and EF (selective attention, divided attention, attentional(re)orienting and disengagement, or attentional shifting).Indeed, these dimensions of attention are not completely over-lapping, either behaviorally or at the level of the brain (seePosner & Rothbart, 2007, for a review). It is also plausible thatintegration across attention-regulating systems underlies thecapacity for incipient social–cognitive abilities such as jointattention, which have been shown to predict later mental statereasoning and global measures of EF tapping inhibition,working memory, and cognitive flexibility (Wade et al.,2016). Attention to internal representations and coordinationof attention systems may therefore facilitate children’s capac-ity to monitor representations of their own and others’ goal-directed behavior, thus laying a foundation on which moresophisticated cognitive abilities can mature (Mundy &Newell, 2007). Similarly, for response suppression/selection,theories that predict how certain responses are selected forover others, and the implications of this for ToM and EF(and indeed for other cognitive systems) are needed. Here, itmay be worth differentiating response selection into perceptu-al (i.e., selecting from the external world) and conceptual (i.e.,selecting from internal representations) domains (Kan &Thompson-Schill, 2004). Developmental models of how sucha system biases the selection of responses based on competingperceptual or representational stimuli—for instance, byrepresenting behavioral goals (Yantis, 2008) or action valuesbased on reward benefits and response costs (Rushworth,2008)—will be helpful in determining how such processesrelate to more complex executive and mentalization abilities.

Finally, if mental processes for comparing internal predic-tions to external events support ToM and EF, what exactly isthe character of this mismatch detection mechanism? How areinternal predictions generated (on the basis of prior beliefs orexperience; means–end or teleological reasoning; or someother generator)? And how do external stimuli become inte-grated into existing mental models to prompt the type of con-ceptual change that allows a child to know that others maypossess information about the world that is different from theirown, and that this information may be false (as in ToM)?Thus, although a constellation of domain-general cognitivefunctions may be recruited in the service of both ToM andEF and may help explain their behavioral and neural overlap,it is also true that these foundational abilities deserve furthertheoretical and empirical attention in their own right.

Conclusion

Converging evidence across subfields of developmental andcognitive neuroscience suggests that ToM and EF share someunderlying neuroanatomical mechanisms, supporting theToM↔EF proposal. These neural networks and their atten-dant nodes are not completely overlapping, however, whicheffectively rules out a strict version of this proposal.Moreover, brain regions generally involved in EF also appearto be recruited during mental state reasoning, and systematicmanipulation of EF has consequences for ToMperformance inboth children and adults, supporting the EF→ToM directionalrelationship. Although support for the ToM→EF link is com-paratively limited, this may reflect a paucity of empirical stud-ies as opposed to null findings. Furthermore, there is someevidence using RSN methods that networks generally impli-cated in ToM may ontogenetically precede and increasinglyinteract with the networks supporting EF over the first 2 yearsof life, and other evidence pointing to critical nodes withintraditional ToM networks that may serve as hubs that integrateand process information across several brain regions. Thus,the ToM→EF proposal deserves further scrutiny. New imag-ing techniques and experimental methodologies, especiallythose adapted for use with children, will be essential in eluci-dating which of these models best explains the developmentallink between ToM and EF. Indeed, consistent with interven-tion studies in children that have shown robust bidirectionalfacilitatory effects of ToM and EF on each another (Kloo &Perner, 2003), both common and discrete neurological mech-anisms may be operative in the maturation of ToM and EF,and these mechanisms may scaffold and reinforce each otherover the course of development. More nuanced theories abouthow basic cognitive processes such as attention, language,self-consciousness, secondary representation, and agency ex-plain the functional overlap between ToM and EF will helpintegrate the fields of cognitive neuroscience and develop-mental psychology and shed light on how shared and uniqueneural mechanisms contribute to these indispensable cognitivefaculties across the lifespan.

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